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TRV-2026-1011Certified recordPeer-reviewed

AI‐Driven Personalized Nutrition: Integrating Omics, Ethics, and Digital Health

Personalized nutrition (PN) aims to prevent and manage chronic diseases by providing individualized dietary guidance based on genetic, metabolic, and lifestyle data. Artificial intelligence (AI) has become a key enabler in PN by analyzing large-scale, multiomics datasets in obesity, diabetes, cardiovascular, and gastrointestinal disorders, where digital twins and health knowledge graphs support personalized interventions. Current findings demonstrate that AI models can guide microbiome-based dietary intervention…

Health · The Trace — both readings · certified 2026-09-07 · v1 · article view · machine-readable

Current reading — gain

AI models analyzing multiomics data can guide microbiome-based dietary interventions and support obesity management to prevent and manage chronic diseases.

Current reading — problem

AI-driven personalized nutrition is limited by algorithmic bias, poor generalizability, and data privacy risks that prevent fair and reliable clinical application.

What this doesn’t fix

Findings are constrained by algorithmic bias, limited generalizability across populations, and data privacy risks, requiring diverse datasets and standardized multicenter validation before clinical use.

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Truvace Impact Record TRV-2026-1011, v1: “AI‐Driven Personalized Nutrition: Integrating Omics, Ethics, and Digital Health.” Truvace, 2026-09-07. /record/TRV-2026-1011 (accessed at citation time). sha256 ef3ad7f4ede09d5e…

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